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Subject Area

Electrical Engineering

Article Type

Original Study

Abstract

Smart city parking systems face significant challenges related to real-time availability updates, security vulnerabilities in RFID-based access, and connectivity issues. To address these limitations, this paper proposes a comprehensive two-stage intelligent parking system that integrates Internet of Things (IoT), Genetic Algorithms (GAs), and Machine Learning (ML) techniques. The system utilizes sensor technologies, such as infrared sensors and ESP8266 controllers, combined with a mobile application to monitor and manage parking space occupancy in real-time efficiently. In the first stage, real-time parking availability is detected through sensor data transmitted to a cloud infrastructure that updates the user interfaces. The second stage employs GAs and vehicle modifications to enable autonomous self-parking, along with dynamic pricing strategies and traffic flow optimization. Additionally, the system offers secure payment options, reservation functionalities, and protections against unauthorized access, ensuring a user-friendly experience. Scalability is achieved through cloud-based management, accommodating growing numbers of users and parking spaces. By integrating reliable sensor data, advanced algorithms, and intuitive mobile applications, the proposed solution enhances occupancy detection accuracy, reduces search times, and improves urban traffic management, paving the way for more efficient and secure parking in smart cities. The main contribution is the development of a novel, integrated two-stage parking management system that synergistically combines IoT sensors, GAs for autonomous self-parking optimization, and machine learning models for precise occupancy detection. This comprehensive approach enhances the reliability and scalability of parking management solutions, incorporating dynamic pricing strategies and advanced security protocols. Consequently, it effectively addresses critical limitations of current systems.

Keywords

Intelligent parking systems, sensors, Internet of Everything, machine learning, RFID, and smart cities.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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